Abstract
This paper presents a simple model of how an animal should best use experience to track a changing environment. The model supposes that the environment switches between good and bad states according to a first-order Markov chain. The optimal sampling behavior is characterized in terms of the stability of runs (the probability that the environment will stay in the same state from one time to the next) and the relative costs of two kinds of errors: sampling and overrun errors. This model suggests further experimental and theoretical problems.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 15-25 |
| Number of pages | 11 |
| Journal | Theoretical Population Biology |
| Volume | 32 |
| Issue number | 1 |
| DOIs | |
| State | Published - Aug 1987 |
Bibliographical note
Funding Information:I thank A. I. Houston and J. R. Krebs for their help and advicew hen thesei deas were in their earliests tageo f developmentI. thank S. Tamm and S. Shettleworthfo r helpingm e to see this problem from an experimentalist’sp erspectiveI. thank E. L. Chamov for his careful reading of the manuscript.T his work was partially supported by NSF Grant No. BSR-8411495to D. W. S., and I thank the NSF for their help.